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黄伟庆,张艳芳,曹籽文,王思叶.基于布隆过滤器的RFID数据冗余处理算法研究[J].信息安全学报,2019,4(3):93-105 [点击复制]
- HUANG Weiqing,ZHANG Yanfang,CAO Ziwen,WANG Siye.Redundant RFID Data Filtering Algorithm Research Based on Bloom Filter[J].Journal of Cyber Security,2019,4(3):93-105 [点击复制]
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| 基于布隆过滤器的RFID数据冗余处理算法研究 |
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黄伟庆1,2,3, 张艳芳2,3, 曹籽文2,3, 王思叶1,2,3
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| (1.北京交通大学, 计算机与信息技术学院, 北京 中国 100044;2.中国科学院信息工程研究所, 北京 中国 100093;3.中国科学院大学网络空间安全学院, 北京 中国 100093) |
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| 摘要: |
| RFID技术作为物联网领域的关键技术，具有广阔的应用前景。然而RFID设备在读取标签信息时会产生大量冗余数据。因此，RFID数据冗余处理的研究对于减少RFID中间件系统负荷、快速检测出入标签有着重要的意义。之前针对RFID数据冗余过滤的研究往往是单维度、静态场景的简单过滤，无法实现复杂场景下标签的出入检测。因此，本文提出一种名为时间距离布隆过滤器（TDBF）的算法，该算法从时间和空间两个维度进行冗余过滤。与常用的时间布隆过滤器相比，该算法兼顾了RFID标签的读取时间和读取距离，极大的降低了数据的冗余问题。在保证漏读率较低的情况下，极大的降低了数据的误读率。同时该算法支持动态场景中移动标签的冗余过滤，能够较好的满足出入监控需求。 |
| 关键词: 布隆过滤器 冗余过滤 数据清洗 射频识别 |
| DOI：10.19363/J.cnki.cn10-1380/tn.2019.05.07 |
| 投稿时间：2019-02-25修订日期：2019-04-19 |
| 基金项目:本课题得到物品管控系统安全方案设计及系统测试（No.Y7V0131104）资助。 |
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| Redundant RFID Data Filtering Algorithm Research Based on Bloom Filter |
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HUANG Weiqing1,2,3, ZHANG Yanfang2,3, CAO Ziwen2,3, WANG Siye1,2,3
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| (1.School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044 China;2.Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China;3.School of Cyber Security, University of Chinese Academy of Sciences Beijing 100093, China) |
| Abstract: |
| As a key technology in the field of Internet of Things, RFID technology has broad application prospects. However, RFID devices generate a large amount of redundant data when reading tag information. Therefore, the research on RFID data redundancy processing is of great significance for reducing the load of RFID middleware system and quickly detecting incoming and outgoing tags. Previous studies on the redundancy filtering of RFID data are often simple filtering of single-dimensional and static scenes, and it is impossible to detect the ingress and egress of tags in complex scenarios. Therefore, this paper proposes an algorithm called Time Distance Bloom Filter (TDBF), which performs redundant filtering from both time and space. Compared with the Time Bloom filter, this algorithm takes into account the reading time and reading distance of the RFID tags, which greatly reduces the redundancy of the data. In the case of ensuring a low miss rate, the false-positive rate of the data is greatly reduced. At the same time, the algorithm supports redundant filtering of mobile tags in dynamic scenarios, which can better meet the requirements of access control. |
| Key words: bloom filter redundant filtering data cleaning Radio frequency identification |
